# v = brutality[k]
line = "{k:<10} & {v:.1f}\% \\\ \hline".format(k=k, v=v)
print(line)
print()
def print_double(data1, data2):
sorted_data1 = sorted_dict(data1)
sorted_data2 = sorted_dict(data2)
iterator = zip(sorted_data1, sorted_data2)
for (k1,v1), (k2,v2) in iterator:
line = r"{k1:<10} & {v1:>5.1f}\% & {k2:<10} & {v2:>5.1f}\% \\ \hline".format(**locals())
print(line)
single = {}
for name in os.listdir(path_single):
hpc = csv2dict(path_single+name)
inps = hpc['instructions'] / hpc['cycles']
single[name] = inps
summary = 0
double = {}
print("~ &", " &".join(sorted(single)), "\\\\")
for bg in sorted(single):
print("{:12}".format(bg), end='')
for fg in sorted(single):
hpc = csv2dict(path_double+bg+'/'+fg)
inps = hpc['instructions'] / hpc['cycles']
ratio = inps/single[fg]
double[bg,fg] = ratio
percents = (1 - ratio)* 100
# if percents < 0:
def perfbars(files, annotations=[], thr=0.01, show=False, output=None, title=None, quiet=False, key_order=None):
p.figure()
num = len(files)
assert num > 0, "please provide at least one path"
if not annotations:
annotations = [basename(f) for f in files]
data = [csv2dict(f) for f in files]
bars = [[] for _ in data]
labels = []
if key_order:
print("WITH KEY_ORDER THRESHOLD IS ALWAYS 0")
thr = 0.0
if not key_order:
key_order = sorted(data[0])
if 'cycles' in key_order:
key_order.remove('cycles')
for k in reversed(key_order):
values = []
for datum, bar in zip(data, bars):
values += [ datum[k] / datum['cycles'] ]
if list(filter(lambda x: x>thr, values)):
labels += [k]
for bar, v in zip(bars, values):
bar += [v]
else:
if not quiet: print("excluding", k)
for b in bars:
if not quiet: print(b, labels)
ind = p.arange(len(labels))
print("ind", ind)
if title:
title=title.replace(r"\n", "\n")
p.title(title, weight="semibold")
## title
# title(" | ".join(map(basename, fnames)))
## bars
for i, bar in enumerate(bars):
p.barh(ind+BARWIDTH*(num-2*i-2)/(2*num), bar, height=BARWIDTH/num, label=annotations[i],
#**styles[i]) #
color=cm.Greys_r((i+0.4)/len(bars)*0.8))
#color=cm.gist_ncar(1-1/num*i), hatch=hatches[i], alpha=0.7)
## reverse legend
# handles, labels = gca().get_legend_handles_labels()
# legend(handles[::-1], labels[::-1], loc='best')
p.legend(loc="best")
## grid
p.grid(lw=1)
## xaxis
xaxis = p.gca().xaxis
# xaxis.set_major_formatter(to_percent)
# xaxis.set_major_locator(MaxNLocator(nbins=4, prune='upper'))
p.xlabel("Avg. number of events per CPU cycle")
# xlim(0,1)
## set aspect
# g = gca()
# g.set_aspect(0.6)
## yaxis
p.yticks(enum_(labels), labels)
p.ylim(-0.5, len(labels)-0.5)
p.tight_layout(pad=0.5)
if output:
p.savefig(output)
if show:
p.show()
